Advances and Applications in Sliding Mode Control systems by Ahmad Taher Azar PDF

By Ahmad Taher Azar

ISBN-10: 3319111728

ISBN-13: 9783319111728

ISBN-10: 3319111736

ISBN-13: 9783319111735

This ebook describes the advances and functions in Sliding mode keep an eye on (SMC) that's everyday as a robust approach to take on doubtful nonlinear platforms. The booklet is equipped into 21 chapters which were organised by means of the editors to mirror a number of the topics of sliding mode regulate. The publication presents the reader with a wide variety of fabric from first rules as much as the present cutting-edge within the zone of SMC and statement provided in a transparent, matter-of-fact sort. As such it really is acceptable for graduate scholars with a simple wisdom of classical keep watch over conception and a few wisdom of state-space tools and nonlinear platforms. The ensuing layout tactics are emphasised utilizing Matlab/Simulink software.

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2013; Lee et al. 2014). One important challenging characteristic of this robot is having the dynamic equations which are nonlinear and demanding to control. To this end, it is crucial to employ a nonlinear controller which is robust with regard to disturbances and uncertainty in order to provide stable walking for biped robots (Andalib Sahnehsaraei et al. 2013). In this regard, sliding mode control is an effectual control method in terms of providing low tracking error in contrast to PID control (Lu et al.

T. E. Serrano Li H, Bai Y, Su Z (2011) Adaptive sliding mode control of electromechanical actuator with improved parameter estimation. In: Proceedings of the IEEE Asian control conference (ASCC). Kaohsiung, Taiwan Liu J, Laghrouche S, Harmouche M, Wack M (2013) Adaptive-gain second-order sliding mode observer design for switching power converters. : Decentralized control of robot manipulators: nonlinear and adaptive approaches. IEEE Trans Autom Control 44(2), 357–363 (1999) Moreno JA (2012) Lyapunov approach for analysis and design of Ssecond order sliding mode algorithms.

In comparison, genetic algorithm optimization operates based upon reproduction, crossover and mutation; however particle swarm optimization functions by means of M. K. J. Mahmoodabadi · F. M. T. Azar and Q. 1007/978-3-319-11173-5_2 43 44 M. Taherkhorsandi et al. a convergence and divergence operator, a periodic leader selection method, and an adaptive elimination technique. When the multi-objective optimization algorithms are applied to the design of the controller, there is a trade-off between the tracking error and control inputs.

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Advances and Applications in Sliding Mode Control systems by Ahmad Taher Azar

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